Tag: python

Felienne interviews Veronika Cheplygina about image recognition. The discussion covers: what exactly constitutes image recognition, including categorizing and segmentation problems; fields where image recognition are currently being applied, including medicine, self-driving cars and security, and future applications. The host and guest also cover how to obtain enough and good datasets, and some of the common […]

Felienne interviews Jeroen Janssens on Data Science. They examine what data science is exactly, particularly exploring how it differs from machine learning and statistics. The episode further considers what skills people need to be great data scientists – skills that are related but not always equal to the skills that programming and software engineering require. […]

We start our discussion with a brief look at what Haskell is and how a pure functional language is different from non-pure languages. We then look at the basic building blocks and the philosophy of the language, discussing concepts such as the lambda calculus, closures, currying, immutability, lazy evaluation, memoization, and the role of data types in functional languages. A significant part of the discussion is then spent on the management of side effects in a pure language – in other words, the importance of monads. We conclude the episode with a look at Haskell’s importance and community today.

In this Episode we talk about dynamic languages for statically-typed minds, or in other words: which are the interesting features people should learn when they go from a langauge such as Java or C# to a language like Python or Ruby. We used Ruby as the concrete example language.

We started the discussion about important features with the concept of dynamically changing an object’s type and the idea of message passing. We then looked at the concepts of blocks and closures. Next in line is a discussion about functions that create functions as well as currying. This lead into a quick discussion about continuations. Open classes, aliasing and the relationship to AOP was next on our agenda.

We then looked considered a somewhat more engineering-oriented view and looked at the importance of testing and what are the best steps of getting from static programming to dynamic programming. Finally, we discussed a bit about the current (as of October 2006) state of dynamic languages on mainstream platforms.

In this Episode, Alexander and Markus talk about scripting languages. Topics include the definition of what a scripting language is, typical usage scenarios, performance issues, programming styles and IDE support. In later Episodes we will talk about more specific topics, such as dynamic typing, reflection, functional programming as well as specific languages such as Ruby.